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8679 findingsmedian surprise 0.0046window 3 days
UNIT / TREND-MONITOR · REV 2.6
[ 3 days window ]
SOURCE: own snapshots
FINDING #6138 · UNIT ID 1329272295
Leonxlnx/unlazy
Anti-laziness skill for AI agents. Core: the Depth Tree method, which splits a task N layers deep and gives every leaf the full time budget of the whole task, so effort multiplies with depth. Grounded in 2025-2026 research on model laziness, underthinking and premature completion.
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SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.000774
ENGAGEMENT0.37
FRESHNESS1.00
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
1% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D
9.67
ACCEL
-1.50
RETENTION
42.9%
PEAK 2026-10-09 · FORK-RETENTION 0.0% · 29 STARS / WINDOW

Author Audience

AUDIENCE
12,456
FOLLOWERS
2,224
OWNER ★
102,324

Engagement Signals

FORKS
289
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 29 / 29 (DIVERSITY 1.00)

Why This Is A Finding

Leonxlnx/unlazy собрал 29 звёзд за окно, тогда как у автора всего 2,224 подписчиков — эффективная аудитория ≈ 12,456. Это даёт surprise-индекс 0.000774 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 0.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация отрицательная — внимание остывает после пика.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 8679 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00-0.00ABOVE 29%
VELOCITY9.675.67+4.00ABOVE 69%
RETENTION42.9%42.4%+0.4 PPABOVE 50%
FORKS289334-45ABOVE 47%
SURPRISE0.000.00-0.00ABOVE 21%